code: def check_data(x, y, data_config):
      assert (
          data_config["past_seq_len"] == x.shape[-2]
      ), "The x shape should be (batch_size, past_seq_len, input_feature_num), \
          Got past_seq_len of {} in config while x input shape of {}.".format(
          data_config["past_seq_len"], x.shape[-2]
      )
      assert (
          data_config["future_seq_len"] == y.shape[-2]
      ), "The y shape should be (batch_size, future_seq_len, output_feature_num), \
          Got future_seq_len of {} in config while y input shape of {}.".format(
          data_config["future_seq_len"], y.shape[-2]
      )
      assert (
          data_config["input_feature_num"] == x.shape[-1]
      ), "The x shape should be (batch_size, past_seq_len, input_feature_num), \
          Got input_feature_num of {} in config while x input shape of {}.".format(
          data_config["input_feature_num"], x.shape[-1]
      )
      assert (
          data_config["output_feature_num"] == y.shape[-1]
      ), "The y shape should be (batch_size, future_seq_len, output_feature_num), \
          Got output_feature_num of {} in config while y input shape of {}.".format(
          data_config["output_feature_num"], y.shape[-1]
      )
  
file_path: analytics-zoo/pyzoo/zoo/chronos/forecaster/utils.py
imports: import torch
  import random
  import numpy
  from torch.utils.data import TensorDataset, DataLoader
  import numpy
  from zoo.orca.data import XShards
label_desc: Use image node_id 5 for calling a global function with example usage: check_data(x, y, data_config) without return types